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Electric vehicle works on stored energy inside the batteries or cells. These units needs to be regulated by cool down or heat up to perform utmost. This temperature regulation also ensure individual battery or cell life. BCS are installed on vehicles to regulate the temperature around battery packs. To ensure maximum performance of these units, numerical simulation is performed and detailed optimization of flow rate as well as flow path into BCS is carried out. All the parts are assembled inside the unit as per defined packaging area or size. Numerical modelling (CFD) is performed to examine the flow path. Flow path is very important to examine, as BCS units consists of condenser. It is very important for condensers to perform efficiently, which means air flow should happen across it appropriately. If sufficient flow is not happening across the condenser, then performance of condensers comes down and optimum temperature around battery packs cannot be maintained.

Cross flow heat exchangers are very common in automotive vehicle thermal management systems. The most important and standard fitment of any vehicle is the radiator, a cross flow heat exchanger for engine cooling systems. As a vehicle manufacturer, selection of a cooling system based on the requirements is very critical especially when the radiators are sourced from multiple sources and of different configurations. So, these different types of radiator have to be compared on the same level for effective selection of heat exchangers. This demands the common methodology to be created to understand the heat exchanger performance with different geometrical input from different sources. In this study, an empirical cum analytical based methodology has been developed for generating the performance characteristics of the louvered fin heat exchanger using the thermal resistance and Number of Transfer Units (NTU) method.

The two major areas of engine development, the automobile industry is concentrating and putting its major product development efforts on are emission control and improved fuel efficiency. These developments either directly or indirectly impact the cooling system requirements significantly. A small change in cooling system requires the vehicle to undergo cooling tests before commercial release to make sure it performs as per requirements. Normally, on an average, 4-5 trials are conducted before clearing the vehicle for production. This involves a lot of time, efforts and resources. The objective of this study is to develop a methodology to predict the cooling system performance analytically and validate the results with experimental data. This study will help in reducing the number of trials thereby saving cost, time and efforts involved. Basic components of cooling system include radiator, charge air cooler and fan.